Executive control processes are needed to regulate the balance between attending to events in one's external environment and attending to introspective processing, including the reliving of past memories and the associated emotions that they evoke. The proposed studies aim to clarify the neural mechanisms that support these specific forms of cognition and that mediate the ability to flexibly shift attentional resources between them. We are specifically interested in evaluating whether the retrieval of a negatively-valenced autobiographical episode will induce an internally-oriented brain state that may obstructively linger when changing task demands require a shift towards prioritizing the processing of incoming sensory stimuli. Our interests are motivated by recent findings in patients with major depressive disorder (MDD), who exhibit a tendency to ruminate about negative past events, difficulty disengaging from these ruminations, and an associated neural system abnormality resulting in an inability to effectively mobilize executive control systems to suppress the internally-oriented default mode network (DMN). This may in turn exert a cost on the performance of goal-directed cognitive operations that depend on monitoring external stimuli and limiting distraction. However, before we can properly characterize these processes in MDD, it is essential that we better understand how the healthy brain enacts executive control to efficiently shift between internally- and externally-focused states, especially in the context of negative affect. To pursue these goals, we have designed an fMRI task paradigm in which participants are cued to vividly recall a negatively-valenced or neutral autobiographical memory and shortly thereafter are tasked with performing an externally-oriented visual working memory task. Our proposed analyses will monitor brain activity, functional connectivity, and behavior as participants shift back and forth between these two very distinct tasks-one requiring self-reflective mentation and the other requiring continuous stimulus processing and decision-making. By training a multivariate classifier model to identify functional connectivity patterns uniquely associated with each task set, we will be able to track the expression of these connectivity signatures over time. This will allow us to test whether the recollection of negative life events disproportionately impairs one's ability to efficiently reconfigure cortical network dynamics during the transition between tasks. Such metrics could eventually be used to aid in the diagnosis of MDD or the identification of those most prone to relapse. Indeed, given current NIMH priorities for treatment development, using such a endophenotype (Miller & Rockstroh, 2013) as a treatment target may warrant high priority.